End of training
Browse files- README.md +14 -14
- adapter_model.bin +1 -1
README.md
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@@ -42,19 +42,19 @@ deepspeed: null
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early_stopping_patience: null
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eval_max_new_tokens: 128
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eval_table_size: null
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-
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flash_attention: true
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps:
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gradient_checkpointing: false
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group_by_length: false
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hub_model_id: error577/be3c53b4-2dbf-4a12-957b-9bf2e80845f8
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hub_repo: null
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hub_strategy: checkpoint
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hub_token: null
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learning_rate: 0.
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load_in_4bit: true
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load_in_8bit: false
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local_rank: null
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@@ -77,7 +77,7 @@ pad_to_sequence_len: true
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resume_from_checkpoint: null
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s2_attention: null
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sample_packing: false
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saves_per_epoch:
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sequence_len: 512
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special_tokens:
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pad_token: </s>
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tokenizer_type: AutoTokenizer
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train_on_inputs: false
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trust_remote_code: true
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val_set_size: 0.
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wandb_entity: null
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wandb_mode: online
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wandb_name: 838ffd28-d356-4c40-a584-abc51f2d4a95
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@@ -105,7 +105,7 @@ xformers_attention: null
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.
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## Model description
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@@ -124,12 +124,12 @@ More information needed
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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### Training results
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| Training Loss | Epoch
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| 2.
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| 2.
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| 2.
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### Framework versions
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early_stopping_patience: null
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eval_max_new_tokens: 128
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eval_table_size: null
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eval_steps: 50
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flash_attention: true
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps: 8
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gradient_checkpointing: false
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group_by_length: false
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hub_model_id: error577/be3c53b4-2dbf-4a12-957b-9bf2e80845f8
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hub_repo: null
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hub_strategy: checkpoint
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hub_token: null
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learning_rate: 0.001
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load_in_4bit: true
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load_in_8bit: false
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local_rank: null
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resume_from_checkpoint: null
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s2_attention: null
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sample_packing: false
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saves_per_epoch: 1
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sequence_len: 512
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special_tokens:
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pad_token: </s>
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tokenizer_type: AutoTokenizer
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train_on_inputs: false
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trust_remote_code: true
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val_set_size: 0.005
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wandb_entity: null
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wandb_mode: online
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wandb_name: 838ffd28-d356-4c40-a584-abc51f2d4a95
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5279
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 2.7769 | 0.002 | 1 | 3.0125 |
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| 2.4637 | 0.1 | 50 | 2.5838 |
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| 2.1737 | 0.2 | 100 | 2.5279 |
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### Framework versions
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adapter_model.bin
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